Authors : Gudimetla Anu Karishma; Bheeshmika Getcha; Dakshanadi Kowsalya; Buddana Durga Vara Prasad; Sai Varshini Rowthula; Mahammad Gouse Mohiddeen

Volume/Issue : Volume 10 - 2025, Issue 12 - December

Google Scholar : https://tinyurl.com/uj5zbnmu

Scribd : https://tinyurl.com/3327anut

DOI : https://doi.org/10.38124/ijisrt/25dec1209

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : Self-Building Project Manager Agent is an intelligent automation platform designed to streamline project initiation and resource aggregation using artificial intelligence. Leveraging large language models and integrated API systems, the agent autonomously collects and organizes essential project resources such as GitHub repositories, YouTube tutorials, relevant research papers, and contextual code snippets based on a user-specified project name and domain. The system also generates AI-assisted research papers summarizing the project’s objectives, technical methodologies, and literature support. A central feature of the platform is its personalized user dashboard, which enables users to log in, manage their generated projects, and securely download complete project packages as zip files. The platform integrates Fast API as the backend framework for handling API communication and authentication, while Next.js powers the dynamic, interactive frontend interface. Data storage and file management are supported through MongoDB and Grid FS, ensuring scalability and reliability in project archiving. By combining intelligent resource retrieval, AI-driven document generation, and fullstack integration, the Self-Building Project Manager Agent provides a unified workspace for students, researchers, and developers. The system effectively reduces the time spent in the preliminary stages of project development by automating research, data collection, and documentation. This innovation bridges the gap between ideation and implementation, enabling users to move from concept to executable prototype seamlessly.

Keywords : AI Project Management, Intelligent Agent, Fast API, Next.js, Research Paper Generation, GitHub API, YouTube API, Lang Chain, Automation, MongoDB, LLM Integration.

References :

1. Wu, T., Liang, P. (2024). Auto Gen: Enabling Next-Generation LLM Applications via Multi-Agent Collaboration. arXiv:2308.08155.
2. Park, J. S., Ouyang, L., Liu, H., et al. (2024). Generative Agents: Interactive Simulacra of Human Behavior. ACM Transactions on Intelligent Systems and Technology.
3. Microsoft Research. (2023). TaskMatrix.AI: A Unified Platform for Multimodal and Agent-based Automation. arXiv:2303.16434.
4. Peng, B., Galley, M., He, X., et al. (2023). Instruction-Following Large Language Models and Autonomous Task Automation. arXiv:2305.17888.
5. OpenAI. (2024). GPT-5 & Autonomous Reasoning Systems: Technical Overview. OpenAI Research Release.
6. Shreya, G., & Narayanan, A. (2023). AI Workflow Automation Using Multi-Agent Systems. Journal of Intelligent Systems, 32(4), 620–635.
7. Zheng, Y., Liu, T., & Ma, X. (2024). LLM-Powered Research Assistants: Automating Analysis, Paper Generation, and Experimentation. IEEE Transactions on Knowledge and Data Engineering.
8. Zhang, Q., Zhao, S., & Li, J. (2023). Autonomous Coding and Documentation Generation Using Large Language Models. IEEE Software, 40(6), 58–67.
9. Jin, C., Wang, H., & Du, S. (2024). Intelligent Project Management Using AI Agents and Workflow Orchestration. Proceedings of the 2024 International Conference on Artificial Intelligence and Applications.
10. MongoDB Inc. (2024). Using MongoDB for AI Workflows, Vector Storage, and Agent Memory. MongoDB Technical Documentation.